Retail

Retail

How data science is impacting the Retail sector.

Data science in Retail

Data Science has seen many applications in retail, with the most common example being Amazon. They are recommending products to customers based on similar users and improving their inventory management and shipping processes through machine learning models that can accurately predict who will order what and when. According to IBM, 62% of retailers say the use of Big Data techniques gives them a serious competitive advantage. Here are some examples of such techniques and their impact on business.

Reduce Inventory Costs

Reducing inventory costs but always having enough products for demand is very hard to do, not to mention in uncertain times like COVID-19 brought us. More than purchase data, we need to take into account external data such as macroeconomic conditions, climate, and social data.

This complex task is suitable for machine learning algorithms since they can adapt to new circumstances and quickly analyze the vast amount of data available.

Boost sales with smarter product placement

Previous sales data can uncover purchase patterns and preferences from your customers through Market Basket Analysis. These findings can help you with suggestions of what items to put next to each other and get customers to purchase more products.

But how can the new health safety guidelines for COVID-19 impact the layout of your products in the store? You might need to rethink some product sections to optimize cleaning time and availability, or even create a zone with extra sanitary measures.

Optimizing such a layout is certainly not an easy task, so you will need all the help you can get!

Build a long-lasting relationship with your clients

Client acquisition is expensive so it's better just to avoid losing them! Having the data from your e-commerce or fidelity card means you can get to know your customers a little better and suggest to them the products they enjoy the most.

Market Basket Analysis will help you identify these preferences, which can be used to create gifts or discounts on certain products which help you build a relationship with them. This will prevent customers from going to your competitors and also contribute to acquiring new clients from your happy customers' positive reviews.

Reduce costs on Customer Support

With customers turning more to a long-distance contact, either via phone or online, you are bound to have your contact channels flooded, possibly losing some customers to your competition while you are at it.

A robust system that can automatically answer most frequent questions and make suggestions to your customers could help you reduce customer support costs in surprising values.

Guarantee return on your investment!

As you may have noticed, some of these applications overlap since they can sometimes impact the same objective. This is why a carefully designed data strategy is important to keep your company working on the top priority objectives and guarantee a return on investment as soon as possible.